Proceedings of 1995 American Control Conference - ACC'95
DOI: 10.1109/acc.1995.533785
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A self-designing receding horizon optimal flight controller

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Cited by 35 publications
(13 citation statements)
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“…The designer can implement various constraints during the optimization such as position and rate saturation on control inputs. Receding horizon model predictive control produces an optimal control sequence for a finite receding time interval [80,81]. The primary drawback of MPC is the computation time required to solve the optimization problem.…”
Section: Control Reconfigurationmentioning
confidence: 99%
“…The designer can implement various constraints during the optimization such as position and rate saturation on control inputs. Receding horizon model predictive control produces an optimal control sequence for a finite receding time interval [80,81]. The primary drawback of MPC is the computation time required to solve the optimization problem.…”
Section: Control Reconfigurationmentioning
confidence: 99%
“…This stage of the methodology was demonstrated on F-16 VISTA simulations, and included both longitudinal and lateral-directional dynamics [20]. Additionally, a version of this methodology was flight tested on the F-16 VISTA [21,22].…”
Section: Parameter Estimationmentioning
confidence: 99%
“…The subobjective could involve driving the control effectors to a preferred position 6 P . A performance index reflecting this objective is given by min7 s = ||W ä ((5-<5 p )|| 1 s…”
Section: Control Sufficiency Branchmentioning
confidence: 99%